Book Reviews: Dams and Development: A New Framework for Decision-Making

2001 ◽  
Vol 3 (3) ◽  
pp. 191-192 ◽  
Author(s):  
Cailin Orr
Keyword(s):  
Decision Making ◽  
New Framework

To Hell with the Cell: The Case for Immersive Statecraft Education

2021 ◽  
Author(s):  
Arvid Bell ◽  
Alexander Bollfrass
Keyword(s):  
Decision Making ◽  
Real World ◽  
Control Cell ◽  
Harvard University ◽  
Simulation Design ◽  
Deep Uncertainty ◽  
Effective Training ◽  
Training And Research ◽  
Negotiation Simulation ◽  
New Framework

Abstract Current wargaming techniques are effective training and research instruments for military scenarios with fixed tools and boundaries on the problem. Control cells composed of officiants adjudicating and evaluating moves enforce these boundaries. Real-world crises, however, unfold in several dimensions in a chaotic context, a condition requiring decision-making under deep uncertainty. In this article, we assess how pedagogical exercises can be designed to effectively capture this level of complexity and describe a new framework for developing deeply immersive exercises. We propose a method for designing crisis environments that are dynamic, deep, and decentralized (3D). These obviate the need for a control cell and enhance the usefulness of exercises in preparing military and policy practitioners by better replicating real-world decision-making dynamics. This paper presents the application of this 3D method, which integrates findings from wargame and negotiation simulation design into immersive crisis exercises. We share observations from the research, design, and execution of “Red Horizon,” an immersive crisis exercise held three times at Harvard University with senior civilian and military participants from multiple countries. It further explores connections to contemporary trends in international relations scholarship.

scholarly journals Integrated Inventory Management Control Framework

2020 ◽  
pp. 147-157 ◽  
Author(s):  
H.R. Ganesh ◽  
P. S. Aithal ◽  
P. Kirubadevi
Keyword(s):  
Decision Making ◽  
Inventory Management ◽  
Performance Indicators ◽  
Management System ◽  
Management Control ◽  
Inventory Management System ◽  
Control Framework ◽  
Brick And Mortar ◽  
And Control ◽  
New Framework

The concept of minimum display quantity (MDQ) is unavoidable in brick-and-mortar retailing format owing to which, retailers need to ensure a minimum level of inventory displayed at each store irrespective of the revenue or inventory turns generated by a particular store. It is observed that majority of bricks-and-mortar retailers in India assume;(a) existing inventory management system is ideal to their store, (b) software solutions record accurate inventory movement, (c) involving store management team in inventory related decision making is risky/biased and most importantly (d) loss of sale due to stockouts is inevitable. Such assumptions and widely followed practice have created a predisposition and mindset in store managers and they believe that their store delivers revenue and profit to the best of its potential with the inventory which is made available to them through existing inventory management system and we cannot avoid a number of instances consumers are unsatisfied due to stockout situations. In this research, we have analysed the existing decision-making process and control systems related to inventory management of a select retailer, attempted to design a new framework and applied the same through an experiment to evaluate the change in (a) overall store profitability and (b) inventory related key performance indicators.

scholarly journals Autonomy, Rationality, and Contemporary Bioethics

2020 ◽  
Author(s):  
Jonathan Pugh
Keyword(s):  
Decision Making ◽  
Informed Consent ◽  
Personal Autonomy ◽  
Rational Beliefs ◽  
Philosophical Work ◽  
Decision Making Capacity ◽  
Important Relationship ◽  
Legal Judgments ◽  
The Relationship ◽  
New Framework

Personal autonomy is often lauded as a key value in contemporary Western bioethics, and the claim that there is an important relationship between autonomy and rationality is often treated as an uncontroversial claim in this sphere. Yet, there is also considerable disagreement about how we should cash out the relationship between rationality and autonomy. In particular, it is unclear whether a rationalist view of autonomy can be compatible with legal judgments that enshrine a patient’s right to refuse medical treatment, regardless of whether ‘… the reasons for making the choice are rational, irrational, unknown or even non-existent’. This book brings recent philosophical work on the nature of rationality to bear on the question of how we should understand autonomy in contemporary bioethics. In doing so, the author develops a new framework for thinking about the concept, one that is grounded in an understanding of the different roles that rational beliefs and rational desires have to play in personal autonomy. Furthermore, the account outlined here allows for a deeper understanding of different forms of controlling influence, and the relationship between our freedom to act, and our capacity to decide autonomously. The author contrasts his rationalist account with other prominent accounts of autonomy in bioethics, and outlines the revisionary implications it has for various practical questions in bioethics in which autonomy is a salient concern, including questions about the nature of informed consent and decision-making capacity.

scholarly journals The Bayesian Prophet: A Low-Regret Framework for Online Decision Making

2020 ◽  
Author(s):  
Alberto Vera ◽  
Siddhartha Banerjee
Keyword(s):  
Decision Making ◽  
Big Data Analytics ◽  
General Technique ◽  
Matching Problems ◽  
Online Matching ◽  
Additive Loss ◽  
Online Decision Making ◽  
Resource Levels ◽  
Greedy Policy ◽  
New Framework

We develop a new framework for designing online policies given access to an oracle providing statistical information about an off-line benchmark. Having access to such prediction oracles enables simple and natural Bayesian selection policies and raises the question as to how these policies perform in different settings. Our work makes two important contributions toward this question: First, we develop a general technique we call compensated coupling, which can be used to derive bounds on the expected regret (i.e., additive loss with respect to a benchmark) for any online policy and off-line benchmark. Second, using this technique, we show that a natural greedy policy, which we call the Bayes selector, has constant expected regret (i.e., independent of the number of arrivals and resource levels) for a large class of problems we refer to as “online allocation with finite types,” which includes widely studied online packing and online matching problems. Our results generalize and simplify several existing results for online packing and online matching and suggest a promising pathway for obtaining oracle-driven policies for other online decision-making settings. This paper was accepted by George Shanthikumar, big data analytics.

A Non-inferiority Framework for Cost-Effectiveness Analysis

2019 ◽  
Vol 35 (4) ◽  
pp. 291-297
Author(s):  
Xuanqian Xie ◽  
Lindsey Falk ◽  
James M. Brophy ◽  
Hong Anh Tu ◽  
Jennifer Guo ◽  
...  
Keyword(s):  
Decision Making ◽  
Cost Effectiveness ◽  
Active Control ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Cost Effective ◽  
Placebo Control ◽  
Decision Framework ◽  
Life Years ◽  
Intervention Cost ◽  
New Framework

AbstractBackgroundTraditional decision rules have limitations when a new technology is less effective and less costly than a comparator. We propose a new probabilistic decision framework to examine non-inferiority in effectiveness and net monetary benefit (NMB) simultaneously. We illustrate this framework using the example of repetitive transcranial magnetic stimulation (rTMS) and electroconvulsive therapy (ECT) for treatment-resistant depression.MethodsWe modeled the quality-adjusted life-years (QALYs) associated with the new intervention (rTMS), an active control (ECT), and a placebo control, and we estimated the fraction of effectiveness preserved by the new intervention through probabilistic sensitivity analysis (PSA). We then assessed the probability of cost-effectiveness using a traditional cost-effectiveness acceptability curve (CEAC) and our new decision-making framework. In our new framework, we considered the new intervention cost-effective in each simulation of the PSA if it preserved at least 75 percent of the effectiveness of the active control (thus demonstrating non-inferiority) and had a positive NMB at a given willingness-to-pay threshold (WTP).ResultsrTMS was less effective (i.e., associated with fewer QALYs) and less costly than ECT. The traditional CEAC approach showed that the probabilities of rTMS being cost-effective were 100 percent, 39 percent, and 14 percent at WTPs of $0, $50,000, and $100,000 per QALY gained, respectively. In the new decision framework, the probabilities of rTMS being cost-effective were reduced to 23 percent, 21 percent, and 13 percent at WTPs of $0, $50,000, and $100,000 per QALY, respectively.ConclusionsThis new framework provides a different perspective for decision making with considerations of both non-inferiority and WTP thresholds.

Modeling of situation assessment in regional air defense combat

2018 ◽  
Vol 16 (2) ◽  
pp. 91-101
Author(s):  
Hai-yan Yang ◽  
Shuai-wen Zhang ◽  
Xu-yu Li
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Bayesian Network ◽  
Particle Swarm ◽  
Flight Path ◽  
Experimental Results ◽  
Situation Assessment ◽  
Swarm Optimization ◽  
Air Defense ◽  
New Framework

The purpose of situation assessment in regional air defense combat is to quickly fuse data as well as to provide commanders with timely support for decision making. We propose a new framework for situation assessment in regional air defense combat, which plays a very concrete role in real combat and follows the combat process. The proposed framework involves three aspects: assessment of the air defense capability of a region; the prediction of an enemy’s invasion route; and the generation of an interception plan. A Bayesian network is used to evaluate and infer the air defense capability of a region. In the network, the calculation of input evidence is based on threat models from radar, the terrain, and anti-aircraft firepower. The weak areas for air defense can be observed when the evaluation is completed. Accordingly, the possible flight path of an enemy invader can be predicted via particle swarm optimization. We build an interception model based on existing attack modes for intercepting enemy aircraft to provide pre-planning for interception. The experimental results prove the feasibility and effectiveness of the proposed method. In particular, the proposed method can contribute to quick decision making in regional air defense combat.

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